Systems for controlling environmental conditions, for example in buildings, are becoming increasingly sophisticated. A control system may at once control heating and cooling, monitor air quality, detect hazardous conditions such as fire, carbon monoxide release, intrusion, and the like. Such control systems generally include at least one environment controller, which receives measured environmental values, generally from external sensors, and in turn determines set-points or command parameters to be sent to controlled appliances.
Communications between an environment controller and the devices under its control (sensors, controlled appliances, etc.) were traditionally based on wires. The wires are deployed in the building where the environment control system is operating, for instance in the walls, ceilings, and floors of multiple rooms in the building. Deploying wires in a building is usually disrupting for the daily operations in the building and costly. Thus, recently deployed environment controllers and devices under their control (sensors, controlled appliances, etc.) are using one or more wireless communication protocol (e.g. Wi-Fi, mesh, etc.) to exchange environmental data.
The environment controller and the devices under its control (sensors, controlled appliances, etc.) are generally referred to as Environment Control Devices (ECDs). An ECD comprises processing capabilities for processing data received via a wireless communication interface and/or generating data transmitted via the wireless communication interface.
The wireless communication interface is generally capable of operating at different data transfer rates. A driver of the wireless communication interface implements a simple algorithm for controlling the data transfer rate, which consists of trying to transfer data at the best possible data transfer rate. If this data transfer rate cannot be sustained, the driver lowers the data transfer rate to a lower value. This process is repeated until the selected data transfer rate can be sustained.
The ECDs may be operating in hostile conditions in terms of wireless data transmission (e.g. in industrial environments), which negatively affects the data transfer rate. Alternatively, the ECDs may be sharing an available wireless spectrum with other devices and competing with these other devices for access to the wireless spectrum, which also negatively affects the data transfer rate. Therefore, the data transfer rate of the ECDs need to be adapted on a regular basis, and the aforementioned process implemented by the driver of the wireless communication interface may be too long and not efficient.
An alternative process may consist in defining a set of rules taking into consideration current conditions for performing a wireless data transfer to select an optimal data transfer rate adapted to the current conditions. However, the parameters affecting the speed of a wireless data transfer are multiple, and are generally inter-related. Thus, the aforementioned set of rules would either by too simple to properly model the conditions for performing a wireless data transfer, or alternatively too complicated to be designed by a human being.
However, current advances in artificial intelligence, and more specifically in neural networks, can be taken advantage of to define a model taking into consideration current conditions for performing a wireless data transfer to select an optimal data transfer rate adapted to the current conditions.
Therefore, there is a need for a new inference server and environment control device (ECD) for inferring an optimal wireless data transfer rate.